Interest in the epidemiology of TB was triggered by the re-emergence of tuberculosis in the early 1990’s with the advent of HIV and falling economic status of many people which subjected them to poverty. The dual lethal combination of HIV and poverty triggered an unprecedented TB epidemic. In this study, we focused on the period 2000-2013 and all the notified data in Kenya was included. Data on estimates of TB incidence, prevalence and mortality was extracted from the WHO global Tuberculosis database. Data was analysed to produce trends for each of the years and descriptive statistics were calculated. The results showed that there was an average decline of 5% over the last 8 years with the highest decline being reported in the year 2012/13. TB continues to disproportionately affect the male gender with 58% being male and 42% being female. Kenya has made significant efforts to address the burden of HIV among TB patients with cotrimoxazole preventive therapy (CPT) uptake reaching 98% AND ART at 74% by the end of 2013. Kenya’s TB epidemic has evolved over time and it has been characterised by a period where there was increase in the TB cases reaching a peak in the year 2007 after which there was a decline which began to accelerate in the year 2011. The gains in the decline of TB could be attributed in part to the outcomes of integrating TB and HIV services and these gains should be sustained. What is equally notable is the clear epidemiologic shift in age indicating reduced transmission in the younger age groups.

1. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
IJPHER
The epidemiology of tuberculosis in Kenya, a high
TB/HIV burden country (2000-2013)
Kipruto H1*,4
, Mung’atu J1
, Ogila K1
, Adem A3
, Mwalili S1
, Masini E2
and Kibuchi E5
1*
Jomo Kenyatta University of Agriculture and Technology, Nairobi Kenya.
2
National Leprosy, Tuberculosis and Lung Disease Program, Ministry of Health, Kenya.
3
Mathematics and Physics Department, Technical University of Mombasa, Kenya.
4
World Health Organization, Kenya country Office.
5
KEMRI-Wellcome Trust Research Programme.
Interest in the epidemiology of TB was triggered by the re-emergence of tuberculosis in the
early 1990’s with the advent of HIV and falling economic status of many people which
subjected them to poverty. The dual lethal combination of HIV and poverty triggered an
unprecedented TB epidemic. In this study, we focused on the period 2000-2013 and all the
notified data in Kenya was included. Data on estimates of TB incidence, prevalence and
mortality was extracted from the WHO global Tuberculosis database. Data was analysed to
produce trends for each of the years and descriptive statistics were calculated. The results
showed that there was an average decline of 5% over the last 8 years with the highest
decline being reported in the year 2012/13. TB continues to disproportionately affect the
male gender with 58% being male and 42% being female. Kenya has made significant efforts
to address the burden of HIV among TB patients with cotrimoxazole preventive therapy
(CPT) uptake reaching 98% and ART at 74% by the end of 2013. Kenya’s TB epidemic has
evolved over time and it has been characterised by a period where there was increase in the
TB cases reaching a peak in the year 2007 after which there was a decline which began to
accelerate in the year 2011. The gains in the decline of TB could be attributed in part to the
outcomes of integrating TB and HIV services and these gains should be sustained. What is
equally notable is the clear epidemiologic shift in age indicating reduced transmission in the
younger age groups.
Keywords: Tuberculosis, HIV, ART, Epidemiology, TB/HIV, Kenya
INTRODUCTION
Tuberculosis (TB) continues to be one of the major
infectious diseases of public health concern globally
WHO (2012). It is caused by bacillus bacteria and the
most common causative organism is the
Mycobacterium tuberculosis. Other causative agents
that are occasionally implicated are Mycobacterium
bovis which is transmitted through contaminated milk
and Mycobacterium africanum, Cadmus et al. (2006).
The transmission of the bacteria is through infectious
aerosolized droplet nuclei generated by coughing,
laughing, talking, sneezing and singing. The ability to
generate infectious aerosolized droplet nuclei is
dependent on the infectivity of the patient with sputum
smear positive patients considered most infectious,
Dooley et al. (1992). Infection with the mycobacterium
does not always lead to development of disease as the
immune system is able to contain the infection and the
bacilli remains dormant.
*Corresponding author: Hillary Kipruto, Jomo
Kenyatta University of Agriculture and Technology,
Nairobi Kenya. Email: kiprutoh@gmail.com
International Journal of Public Health and Epidemiology Research
Vol. 1(1), pp. 002-013, October, 2015. © www.premierpublishers.org. ISSN: 2167-0449
Research Article

2. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Kipruto et al. 002
The risk of infection is dependent on the extent to which
exposure happens; longer durations of exposure to
infected persons who are not on treatment increases
the chance of infection, Dooley et al.(1992). The most
at risk to develop TB include children under five, the old
and those who are immunosuppressed, WHO (2012).
Globally, the World Health Organization (WHO)
estimates that 2 billion people, or 1/3 of the world’s
population, are infected with (Mycobacterium
tuberculosis) the bacillus that causes tuberculosis (TB).
In 2013, there were 9 million incident cases with 1.5
million people dying of TB, making it the leading
infectious cause of death worldwide, WHO (2014).
Globally, the African region contributes 26% of the TB
burden making the region the second after Asia which
contributes 59% of the Global case load, WHO (2012).
Kenya is among the twenty two (22) TB high burden
countries in the world which contribute 80% of the
global TB burden, WHO (2012). The absolute number
of TB cases notified has increased more than tenfold
since 1990 while the TB incidence has increased from
below 50 per 100,000 in 1990 to 329 per 100,000
population for all forms of TB in 2008, DLTLD (2013).
The HIV epidemic is the single most contributing factor
for this massive increase in the burden of TB in Kenya.
From the Kenya AIDS Indicator Survey 2013, the
prevalence of HIV in Kenya currently stands at 5.6%,
NASCOP (2013), while the TB HIV co-infection rate
was at 35% in 2014, NLTLD (2014). To combat the
challenges of TB epidemic in Kenya there has been
massive scale up of both treatment and diagnostic
facilities. In 2013, diagnosis and treatment of TB was
carried out by general health care workers in 1,900 TB
diagnostic centres and over 4,300 TB treatment centres
in Kenya DLTLD (2013). This translates to one
diagnostic centre per 37,634 populations and one
treatment centre per 18,411 populations DLTLD (2013).
Diagnosis of TB is through sputum smear microscopy
for new smear positive cases. Smear negative cases
are diagnosed via a diagnostic algorithm as per the
national TB guidelines DLTLD (2013). The diagnosis of
extra pulmonary TB is based on clinical suspicion and
the collection of appropriate specimens for TB
bacteriology where this is feasible DLTLD (2013).
Kenya developed a medium term TB control strategic
plan covering the period 2011-2015 which is modelled
along the WHO Stop TB Strategy. The global targets of
TB control are to achieve at least 70% TB case
detection rate and 85% treatment success rate, WHO
(2006).
Kenya has made good progress in the fight against TB;
TB Case detection rate (CDR) reached 79% in 2013,
the treatment success rate was 89% in 2013. By the
end of 2014, 95% of TB patients were tested for HIV
against a national target of 95%, NTLD (2014). Despite
this progress, major problems still remain as close to
21% of all incident TB cases are not detected, the
significant delays in TB diagnosis facilitates TB
transmission and is associated with a higher frequency
of the poor sequel of TB and the emerging problem of
drug resistant tuberculosis DLTLD (2013). There are
concerns that inadequate infection control measures in
health care settings may be facilitating the transmission
of TB to health care workers and patients which has
significant consequences for vulnerable groups such as
HIV infected persons, DLTLD (2013). The emergence
of multidrug-resistant Mycobacterium tuberculosis
(MDR-TB) worldwide poses a serious problem to the
treatment of tuberculosis. These MDR strains are at
least resistant to two most important primary
chemotherapeutic agents rifampicin and isoniazid,
WHO (2003) which require treatment with more costly
and more toxic second-line drugs.
To understand TB epidemiology, there is need to
consider the changes in the trends of the burden of TB
disease over a period of time. The main indicators for
the burden of TB disease include; incidence,
prevalence and mortality, WHO (2013). These
estimates have been derived from WHO databases on
TB. Data on TB prevalence and mortality are hardly
available due to low coverage of the civil registration
systems in the country. Kenya is currently (2015)
undertaking a TB national prevalence survey (the last
TB prevalence survey was conducted in 1956).
There is currently no nationally representative vital
registration system with standard ICD-10 coding in
place in Kenya. Less than half of deaths are recorded,
and approximately 10% of deaths receive any ICD code
(CRS, 2014). Results from a prevalence survey and
vital registration systems can be used to assess the
current levels of TB disease and mortality and could
also provide important evidence about the effectiveness
of current TB programmatic efforts and actions needed
to improve TB care and control.
Sitienei et al. (2013) has noted that the evolution of TB
epidemiology in Kenya has mainly been guided by a
number of factors which include but not limited to
economic and environmental factors and the
comprehensive TB control strategies that have been
implemented by the Government of Kenya.
In this paper we describe the epidemiological evolution
of TB in Kenya over the last 14 years with focus of TB
burden measures; prevalence, incidence, mortality and
notifications over the years.
MATERIALS AND METHODS
This study was carried out through detailed and
extensive review of existing TB/HIV data estimates

3. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Int. J. Public Health Epidemiol. Res. 003
from the Global TB database
(http://who.int/tb/country/data/download/en/). This data
was further augmented from the National TB control
program databases. The Kenyan National TB control
program is well known for maintaining a robust
surveillance system which maintains data on
notification from the whole country. The Country has
consistently reported the surveillance data to the World
Health Organization which then facilitates the
production of yearly country profiles.
The national TB surveillance system in Kenya (TIBU)
is an electronic case based system that enables
availability of real time information on all TB patients in
the Country. Data is entered into a tablet by sub-
County TB coordinators from TB facility registers during
routine monthly support supervision visits in the health
facilities. The data is then electronically transmitted to
the national database. This electronic system
commenced in 2012, replacing the previous paper
based system where the districts would on a quarterly
basis aggregate all data from health facilities before
transmission to the regional and national levels.
After retrospectively extracting the data from the Global
WHO database on estimates of prevalence, incidence
and mortality together with the notification data from the
National TB databases for the period (2000-2013), the
data was subjected to exploratory data analysis (EDA)
to look at the emerging trends that was inherent in the
data. The datasets that did not have all the requisite
variables were omitted from the analysis. The data was
managed using MS access and excel was used to
create graphs and tables to depict the changes in TB
epidemiology over the years.
The trends in case notification rates were obtained
using total TB cases notified and population estimates
from the Kenya National Bureau of statistics. The data
was stratified by year, child/adult (<14 years and >15
years), gender, HIV test, disease type and age group.
In Kenya, the policy for diagnosis of TB is that, all
presumed TB cases with signs and symptoms of TB
are sent to the laboratory for collection of sputum
specimen and examination in the laboratory for
presence or absence of tubercle bacilli. Those whose
specimens turn positive for tubercle bacilli are classified
as smear positive, while those who are smear negative
may be commenced on treatment if they fit the clinical
diagnostic criteria or having been diagnosed for TB
based on an abnormal chest x-ray. Before the patients
are started on TB treatment, patients are provided with
information and advantages of HIV testing and those
who consent are provided with HIV testing according to
the national guidelines. Further treatment and diagnosis
for Tuberculosis in Kenya is free and the government
bears the costs of both diagnosis and procurement of
quality assured anti TB medicines.
RESULTS
Burden of TB Disease
Burden of disease is looked at from 3 contexts;
incidence, prevalence and mortality. Analysis of the
trends in estimates of TB incidence (Figure 1) suggests
a consistent decline in new TB cases over time, with
the decline in TB cases starting in 2005 following the
decline in TB/HIV cases which started in 2004. After
peaking in 2006, there has been a slowing in the rate of
decline in estimates of TB prevalence (Figure 2). TB
mortality estimates suggest an increase in TB deaths in
2011-2012 (Figure 3). However, the wide confidence
intervals indicate considerable uncertainty in the
estimates, suggesting the need for other more direct
methods to measure prevalence and mortality.
With regards to deaths occurring to HIV positive TB
patients there has been a consistent decline in the
estimated TB-related deaths among people living with
HIV (Figure 4). This could be attributed to interventions
in both HIV and TB programs beginning to bear fruits
and could need to be further sustained.
TB Case Notifications
In Kenya, the number of notified TB cases (all forms)
increased from approximately 95,000 cases in 2003 to
a peak of over 116,000 cases in 2007 (Figure 5). After
2007, the number of notified TB cases steadily declined
until 2013, when the number of notified TB cases was
approximately 89,000 – the lowest it has been in over a
decade. Approximately 10,000 fewer cases were
reported in 2013 compared with 2012. This trend is
consistent with the trend of incidence and prevalence
which has been observed in (Figures 1 & 2) above.
The case notification rate for all TB cases (new and
retreatment) shows three distinct trends (Figure 6).
From 2000 to 2004, the TB case notification rate
increased steadily; from 2004 to 2006, rates remained
constant; and from 2006 to 2013, rates steadily
declined, with rates in 2013 lower than those recorded
in 2000 (Figure 6). Based on national data, the case
notification rates fell especially quickly between 2011
and 2013, decreasing approximately 8% and 12% each
year, respectively (Table 1); for all years, notification
rates based on Kenyan data are slightly higher than
WHO estimates (Figure 6) and this may be explained
by use of different population estimates.
Case notification rates were calculated using population
estimates from Kenya’s 2009 census (years 2009-
2013) and updated population estimates from the 1999
census (years 2003-2008). Changes in population
estimates between 2008 and 2009 did not appear to
have a large effect on national level case notification
rates.

4. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Kipruto et al. 004
Figure 1. Tuberculosis incidence 2000-2012
Figure 2. Tuberculosis prevalence 2000-2012
Figure 3. Tuberculosis mortality 2000-2012
As shown in Figure 7, the percentage of new childhood
and adult TB cases has remained consistent between
2008 – 2012.The ratios are fairly consistent with the
rates that have been proposed by WHO in their
standards and benchmarks tool which suggests that the
data collected at the national level have a high level of
external consistency if the percentage of children
diagnosed with TB ranges between 5-15% in low - and
middle-income countries, WHO (2014).
TB Cases by Disease Type
The relative numbers of new bacteriologically confirmed
(smear positive) cases and extrapulmonary TB cases

5. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Int. J. Public Health Epidemiol. Res. 005
Figure 4. TB deaths among HIV patients 2000-2012
Figure 5. TB notifications 2003-2013
Figure 6. TB notification rates: 2000-2012
have remained fairly consistent over time (Figure 8).
The percentage of new cases that are bacteriologically
confirmed ranged from 37.3% to 43.0% between 2003
to 2012, fluctuating slightly from year-to-year. The
percent of new cases that are extrapulmonary,
however, increased gradually since 2003 but
maintained a narrower range: 15.1% to 18.2% (Figure
8). This slight increase may result in a reduction in TB
transmission because there are fewer pulmonary TB
cases in the community. Further, when smear positive
new cases are compared to extrapulmonary TB, it
shows that the percentage range of extra-pulmonary is
between 26% and 31% over the years and has
remained stable in this range (Figure 9).

6. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Kipruto et al. 006
Table 1. Change in Notified TB cases (all
forms), Kenya, 2003-2012
Year
National TB case
notification rate
(per 100,000)
% Δ from
previous
year
2000 210.8
2001 233.2 10.6%
2002 254.8 9.3%
2003 287.3 12.7%
2004 309.6 7.8%
2005 308.5 -0.4%
2006 318.7 3.3%
2007 313.9 -1.5%
2008 288.0 -8.2%
2009 281.2 -2.4%
2010 263.6 -6.2%
2011 251.0 -4.8%
2012 230.9 -8.0%
2013 203.1 -12.1%
Figure 7. TB cases: Adults versus children
Figure 8. Percent of new bacteriologically confirmed (smear positive) and extrapulmonary TB cases out of all new cases,
Kenya, 2003 – 2012.
TB Cases by Age
The largest number of TB cases occurred among
young adults (Figure 10), with the most cases reported
for adults aged 25-34 years, followed by adults aged
35-44 and 15-24 years; this indicates that HIV
continues to be a major driver of the TB epidemic in
Kenya. The average age of TB cases in 2012 and 2013

7. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Int. J. Public Health Epidemiol. Res. 007
Figure 9. Pulmonary versus extrapulmonary TB- all new cases
Figure 10. All TB cases by age group- Kenya, 2008-2012
was 33.7 and 37.7 years, respectively; these are the
only years for which case-based data are available.
The fewest cases were reported in children aged 0-4
years.
Age- and sex-specific case notification rates
Figures 11a and 11b show that among all age groups,
except for children (0-15 years) and young adults (15-
24 years), males had higher TB case notification rates
than females. For children and young adults, rates of
new TB disease were equal between males and
females. For both males and females, adults aged 35-
44 years had the highest rates of new TB disease;
however, rates of TB among males in this age group
were approximately 30% greater than rates of TB for
females in the age group.
Differences between males and females by age group
remain, but are less pronounced for new smear positive
TB case notification rates (Figures 12a and 12b). In
particular, for males, 35-44 and 25-34 year olds have
the highest rates for smear positive TB, while 35-44
and 45-54 year olds have the highest rates for all forms
of new TB.
Overtime there has been a small decrease in case
notification rates for all new cases and all new smear
positive cases for both males and females (Figures 11a
and 11b, 12a and 12b). Children and young adults (15-
24 years) saw the most minimal change over time.
Adult’s aged 64 years and above were the only group
to experience increases in TB cases rates.
From the age sex distribution (figures 13-16), it is clear
the most vulnerable age group is that of 15-44, the most
vulnerable group being those aged 15 to 44 the most
economically productive segment of the population.

8. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Kipruto et al. 008
Figures 11a and 11b. Case notification rates per 100,000 among males and females in Kenya from 2008 – 2012.
Figures 12a and 12b. New smear positive case notification rates per 100,000 among males and females in Kenya from 2003 –
2012.
It further shows that those mostly affected are in the
age group 25-34 years. Interesting observation though
is depicted in (figure 13) which shows that there is a bi-
modal peak at age 15 and 25 years of age amongst the
female smear positive TB cases.
National-level TB data disaggregated by age (Figures
12-16) suggest that although the rate of TB in
(12a)
(12b)

9. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Int. J. Public Health Epidemiol. Res. 009
Figure 13. Distribution of females with smear positive TB per age group
Figure 14. Distribution of males with smear positive TB per age group
Figure 15. Distribution all forms of TB for females per age group
the elderly (≥64) has been consistently lower than rates
among middle-aged adult males or females (i.e., 35-44
and 45-54 age groups), it has gradually increased while
rates in younger groups have declined.
TB in High Risk Groups
In Kenya, data on TB in high risk groups are largely
available only about persons living with HIV/AIDS. HIV
remains the predominant risk factor for developing TB
in Kenya. The TB programme has continued to
successfully test more TB cases for HIV over time.
Although rates of HIV remain high among persons with
TB who know their status, more than one-third of TB
cases have HIV, HIV prevalence among TB cases has
been decreasing (Figure 17). There has been

10. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Kipruto et al. 010
Figure 16. Distribution all forms of TB for males per age group
Figure 17. The percentage of TB cases who are tested for HIV, and the percentage of TB cases tested for HIV who are
HIV positive – Kenya, 2008-2012.
Figure 18. CPT and ART uptake in Kenya 2005-2012
significant effort to reduce the burden of HIV among TB
patients through the implementation of TB/HIV
collaborative interventions with the main focus being
provision of CPT and ART to HIV positive TB patients.
There has been significant increase in CPT uptake from
44% in 2005 to 97% by the end of 2012 while ART
uptake increased form a low figure of 17% in 2005 to
74% by the end of 2012 (Figure 18).

11. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Int. J. Public Health Epidemiol. Res. 011
DISCUSSION
The burden of TB disease in Kenya has shown
consistent decline in the last 8 years. This result is
consistent with the findings by Sitienei et al. (2013).
The key disease burden measures incidence,
prevalence and mortality has shown marked decline
over the last couple of years, however, prevalence and
mortality have high levels of uncertainty WHO (2012).
Although mortality estimates have high levels of
uncertainty, there has been marked decline in the
estimates of TB deaths among the HIV patients. This in
part could be attributed to high HIV testing and initiation
of ART treatment among HIV positive patients WHO
(2012).
It is expected that with a robust surveillance system,
notifications should provide good approximations to TB
incidence DLTLD (2013). Kenya over the last 14 years
has notified cumulatively 1,378,592 TB cases DLTLD
(2013). Year by year trend has shown that Kenyan TB
epidemic peaked in the year 2007 and has been on a
decline since then with an average decline of 5% over
the last 8 years. The highest decline in the TB case
notification was reported between the years 2012-2013
at 12%. There has been consistent trend in the case
notification rates from both the Kenyan TB data and
WHO estimates DLTLD (2013).
In this paper, it has been further demonstrated that the
proportion of childhood TB has remained fairly
consistent over the years. With more attention currently
being directed at childhood TB through better
diagnostic tools and improvement of surveillance
systems it could reduce the gap in understanding
childhood TB epidemiology, (Glaziou et al. (2015),
WHO (2013)).
In Kenya, a large proportion of TB has been those who
have been confirmed to have TB using smear
microscopy examination with this proportion ranging
(37-43) %, the extra-pulmonary ranges from (15-18)%
and the smear negative TB cases ranging between (33-
42)%.
Kenya began the disaggregated reporting for age and
sex in the year 2008, while adopting the case based
surveillance system in the year 2012 DLTLD (2013).
The disaggregation has clearly shown that tuberculosis
continues to take greater toll on those in the age groups
25-44 years, this being the most economically
productive group. The average age of a TB patient has
increased from 33.7 to 37.7 between the year 2012 and
2013. Fewer children aged 0-4 years have consistently
been reported to have tuberculosis.
From the age sex case notification rates it can be seen
that tuberculosis continues to be a male disease with
rates in males being approximately 1.5 times higher
than in female in the most productive age groups 25-64
years. This trend is similar for both all forms of TB and
smear positive. It was however, noted that the age sex
distribution for smear positive TB was bimodal for
females while unimodal for males. This result is
consistent with results in Sitienei et al. (2013).
However, for all forms of TB the peakedness of the
distribution is unimodal at the same age groups 25-34
years. At present there is no plausible explanation for
the difference in the age sex distribution peakedness
for smear positive TB Sitienei et al. (2013). It can
however be hypothesized that it could be because of
early sexual activity in female which predisposes them
to HIV and consequently tuberculosis. There is thus
need for further studies to explain the difference. Other
possible hypothesis that have been advanced include
biological differences in the risk of infection and
subsequent TB disease Thorson et al. (2007),
differences due to gender roles in different communities
which predisposes men to TB disease (Borgdorff et al.
(2000), Connolly and Nunn (1996)) and the hypothesis
that it could be that women access services to a greater
extent than men in some settings or that disease
progression could be slower on average in women
Glaziou et al. (2015).
Sitienei et al (2013) showed that HIV is the single most
important factor that caused resurgence of TB in Kenya
and there is a twin relationship between HIV and TB.
This historical twin relationship has been shown by
K’Oyugi and Muita (2002). To understand TB
epidemiology in Kenya, understanding the close
relationship between TB and HIV is critical. The data
from the surveillance system show that upon the
adoption in Kenya of the WHO interim policy on TB/HIV
collaborative activities in 2004, WHO (2004) with Kenya
adopting the policy in 2005. The HIV testing rose from
83 to 94% with HIV sero prevalence declining from 45%
to 38% by the end of 2012. It had further been shown
that those countries with high HIV prevalence have also
high burden of TB. Narain and Lo (2004). Given the
role HIV plays in the development of TB disease
provision of ART and isoniazid (INH) prophylaxis has
increasingly played the role in the prevention of TB in
individuals with HIV and latent TB infection. (Glaziou et
al. 2015, Straetemans et al. 2010, Glaziou et al. 2011).
Kenya has made significant strides in addressing the
dual burden with 74% of the HIV positive TB patients
accessing ART within TB clinics free of charge from the
government by the end of 2012 DLTLD (2013).
The association between poverty and tuberculosis has
been well established and widespread in literature of
TB risk factors. It has been shown that TB prevalence
is significantly higher among people living below the
poverty line compared with those above the poverty line
and the situation is even more dire among the
marginalised people, where TB could be 1.5 times
more prevalent Muniyandi and Ramachandran (2008).
Further, it has been shown that TB can contribute to
moving individuals into poverty by reducing patients’
physical strength and ability to carry on normal routine

12. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Kipruto et al. 012
work (Patton and Ng, 2006; Sagbakken, 2008; WHO,
2005; Hansel et al., 2004).
CONCLUSION
Kenya’s TB epidemiology has evolved over time and it
has been characterised by a period where there was
increase in the TB cases reaching a peak in the year
2007 after which there was a decline which began to
accelerate in the year 2011. The gains which have
been witnessed should be sustained. What is equally
notable is the clear epidemiologic shift in age indicating
reduced transmission in the younger age groups.
All indications are that the TB epidemic in Kenya is on a
downward trend and the country is on course to halting
the beginning to reverse the effects that the epidemic
has caused.
To sustain the gains made in containing TB in Kenya,
efforts must also be made in addressing the risk factors
majorly HIV and what has been demonstrated that the
burden of HIV on TB patients has been addressed in
the country but focus should be on universal access to
ART for those who are eligible and access to the INH
prophylaxis.
Further, to sustain the gains social determinants in
health must be addressed given that TB affects the
most vulnerable in the population and should include
strengthening partnership across all the sectors that are
involved. Further systematic analysis should be carried
out to understand the socio economic dynamics of TB
patients in order to address the well-being of the TB
patients. Kenya is on course to achievement of
millennium development goals (MDGs) of halting and
beginning to reverse the incidence and prevalence to
tuberculosis.
To better understand mortality, greater focus should be
given to improvement of mortality statistics though
strengthening of collaboration with the civil registration
system in the country and supporting the improvement
in the capacity to certify and code cause of death in
health facilities and consider initiation of verbal
autopsies to obtain an understanding of cause of death
amongst those deaths which occur in the community (at
home).
REFERENCES
Borgdorff MW, Nagelkerke NJ, Dye C, Nunn P (2000).
Gender and tuberculosis: A comparison of
prevalence surveys with notification data to explore
sex differences in case detection. Int J Tuberc
Lung Dis 4:23–132.
Cadmus S, Palmer S, Okker M, Dale J, Gover K (2006)
Molecular analysis of human and bovine tubercle
bacilli from a local setting in Nigeria. Journal of
clinical microbiology 44: 29–34.
CRS (2014). Annual Vital Statistics Report.
Government of Kenya, Nairobi
Connolly. M, Nunn P (1996).Women and tuberculosis.
World Health Stat Q49: 115– 119.
DLTLD (2009). Division of Leprosy, TB and Lung
Disease Annual Report. Nairobi: Kenya Ministry of
Health.
DLTLD (2013). Division of Leprosy, TB and Lung
Disease Annual Report. Nairobi: Kenya Ministry of
Health.
Dooley SW, Villarino ME, Lawrence M, Salinas L, Amil
S, Rullan JV, Jarvis WR, Bloch AB, Cauthen GM
(1992). Nosocomial transmissions of tuberculosis in a
hospital unit for HIV-infected patients .Journal of the
American Medical Association.; 267:2632-2634
Glaziou P, Floyd K, Korenromp EL, Sismanidis C,
Bierrenbach AL, Williams BG, Atun R, Raviglione M.
(2011). Livessaved by tuberculosis control and
prospects for achieving the 2015 global target
for reducing tuberculosis mortality.Bull World Health
Organ 89:573–582
Glaziou P, Sismanidis C, Floyd K, Raviglione M (2015).
M Cold Spring Harb Perspect Med 2015); 5:a017798
Hansel NN, Wu AW, Chang B, Diette GB (2004):
Quality of life in tuberculosis: patient and provider
perspectives. Quality of life research: an international
journal of quality of life aspects of treatment, care
and rehabilitation, 13(3):639-652.
K’Oyugi BO, Muita J (2002). "The impact of a growing
HIV/AIDS epidemic on the Kenyan children."AIDS,
public policy and child well-being 2002.
Sagbakken M, Frich JC, Bjune G (2008). Barriers and
enablers in the management of tuberculosis
treatment in Addis Ababa, Ethiopia: a qualitative
study.BMC Public Health, 8:11.
Straetemans M, Bierrenbach AL, Nagelkerke N,
Glaziou P, van der Werf MJ (2010). The effect of
tuberculosis on mortality in HIV positive people: A
meta-analysis. PLoS ONE 5:e15241
Sitienei J, Nyambat V, Borus P, (2013). “The
Epidemiology of Smear Positive Tuberculosis in
Three TB/HIV High Burden Provinces of Kenya
(2003–2009),” Epidemiology Research
International, vol. 2013, Article ID 417038, 7 pages,
2013.doi:10.1155/2013/417038
Muniyandi M, Ramachandran R (2008): Socioeconomic
inequalities of tuberculosis in India.
Expert Opin Pharmac other, 9 (10):1623-1628.
NASCOP (2013). Kenya Aids Indicator Survey. Nairobi:
Kenya Ministry of Health.
Narain JP, Lo YR (2004). Epidemiology of HIV-TB in
Asia.Indian Journal of Medical Research.120
(4):277–289.
NLTLD (2014). National Leprosy, TB and Lung Disease
Program Annual Report. Nairobi: Kenya Ministry of
Health.
Paton NI, Ng YM (2006) Body composition studies in
patients with wasting associated with tuberculosis.

13. The epidemiology of tuberculosis in Kenya, a high TB/HIV burden country (2000-2013)
Int. J. Public Health Epidemiol. Res. 013
Nutrition (Burbank, Los Angeles County, Calif)
22(3):245-251.
Thorson A, Long NH, Larsson LO (2007). Chest X-ray
findings in relation to gender and symptoms: A study
of patients with smear positive tuberculosis in
Vietnam. Scand J Infect Dis 39: 33–37.
WHO (2003). Treatment of tuberculosis: guidelines for
national programmes, 3rd ed. Geneva,
(WHO/CDS/TB/2003.313).
WHO (2004) Interim policy on collaborative TB/HIV
activities , 1st ed. Geneva, World Health
Organization.
WHO (2006). The STOP TB Strategy. Geneva: WHO.
WHO (2012).Global Tuberculosis Surveillance Report.
Geneva: WHO.
WHO (2014).Global Tuberculosis Surveillance Report.
Geneva: WHO.
WHO (2005): Addressing poverty in TB control: Options
for national TB control programs. Geneva: World
Health Organization.
Accepted 10 September, 2015.
Citation: Kipruto H, Mung’atu J, Ogila K, Adem A,
Mwalili S, Masini E, Kibuchi E (2015). The
Epidemiology of Tuberculosis in Kenya, a High TB/HIV
burden Country (2000-2013). International Journal of
Public Health and Epidemiology Research, 1(1): 002-
013.
Copyright: © 2015 Kipruto et al. This is an open-
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
cited.